Using artificial neural network models to assess water quality in water distribution networks
| dc.contributor.author | Cuesta Cordoba, Gustavo Andres | cs |
| dc.contributor.author | Tuhovčák, Ladislav | cs |
| dc.contributor.author | Tauš, Miloslav | cs |
| dc.coverage.issue | 1 | cs |
| dc.coverage.volume | 70 | cs |
| dc.date.issued | 2014-04-30 | cs |
| dc.description.abstract | The purpose of the research is to assess chlorine concentration in WDS using statistical models based on ANN in combination with Monte-Carlo. This approach offers advantages in contrast to the generally use methods for modeling of chlorine decay in drinking water systems until now. The model was tested on one specific location using the hydraulic and water quality parameters such as flow, pH, temperature, etc. The model allows forecasting chlorine concentration at selected nodes of the water supply system. The results obtained in these selected nodes allow then to compare the chlorine concentration with EPANET in the system under assessment. | en |
| dc.description.abstract | Článek popisuje navržený model pro posuzování koncentrace chloru ve vodovodní síti využívající statistických modelů založených na umělých neuronových sítích v kombinaci s metodou Monte-Carlo. | cs |
| dc.format | text | cs |
| dc.format.extent | 399-408 | cs |
| dc.format.mimetype | application/pdf | cs |
| dc.identifier.citation | Procedia Engineering. 2014, vol. 70, issue 1, p. 399-408. | en |
| dc.identifier.doi | 10.1016/j.proeng.2014.02.045 | cs |
| dc.identifier.issn | 1877-7058 | cs |
| dc.identifier.orcid | 0000-0002-2551-9226 | cs |
| dc.identifier.other | 108425 | cs |
| dc.identifier.scopus | 6506683395 | cs |
| dc.identifier.uri | http://hdl.handle.net/11012/194720 | |
| dc.language.iso | en | cs |
| dc.publisher | Elsevier | cs |
| dc.relation.ispartof | Procedia Engineering | cs |
| dc.relation.uri | https://www.sciencedirect.com/science/article/pii/S1877705814000472 | cs |
| dc.rights | Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 Unported | cs |
| dc.rights.access | openAccess | cs |
| dc.rights.sherpa | http://www.sherpa.ac.uk/romeo/issn/1877-7058/ | cs |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/ | cs |
| dc.subject | water distribution systems | en |
| dc.subject | chlorine decay | en |
| dc.subject | artificial neural networks | en |
| dc.subject | Monte Carlo Method | en |
| dc.subject | vodovodní sítě | |
| dc.subject | chlor | |
| dc.subject | umělé neuronové sítě | |
| dc.subject | metoda Monte-Carlo | |
| dc.title | Using artificial neural network models to assess water quality in water distribution networks | en |
| dc.title.alternative | Využití modelů umělých neuronových sítí k hodnocení kvality vody ve vodovodních distribučních sítích | cs |
| dc.type.driver | conferenceObject | en |
| dc.type.status | Peer-reviewed | en |
| dc.type.version | publishedVersion | en |
| sync.item.dbid | VAV-108425 | en |
| sync.item.dbtype | VAV | en |
| sync.item.insts | 2025.02.03 15:46:30 | en |
| sync.item.modts | 2025.01.17 15:34:59 | en |
| thesis.grantor | Vysoké učení technické v Brně. Fakulta stavební. Ústav vodního hospodářství obcí | cs |
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